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In this work, the authors propose to harness the advantages of behavioral programming as a new technique for designing rule-based conversational agents.

To examine the study’s hypotheses, the authors perform a first-of-its-kind user study through which the authors examine how potential designers, both expert designers, computationally-oriented designers, and otherwise, leverage behavioral programming (BP) and dialog graphs for designing conversational agents (CAs). The authors also use two standard CA settings common in the literature: designing a CA representative for a user in an online dating service and a non-character player in a role-playing game (RPG).

The study’s results indicate that BP can be successfully utilized by computationally-oriented designers, with or without prior knowledge in CA design, and can facilitate the design of better CAs (i.e. more accurate and more robust). However, to capitalize on these potential advantages, designers may be required to devote more time to the design process and are likely to encounter higher temporal demand levels. These results suggest that BP, which was initially proposed and evaluated in the general context of software design, can constitute a valuable alternative to the classic rule-based CA design technique commonly practiced today.

An important limitation of this study is the relatively small participant pool. While the authors do plan to extend this study in the future, the current coronavirus disease 2019 (COVID-19) situation makes it ever more complex to conduct formal user studies of this kind. It is, however, important to note that despite the low number of participants, many of the results are found to be statistically significant.

The authors plan to continue this line of work and conduct human studies for additional design techniques in other popular agent-based settings. Specifically, the authors seek to explore how people of different backgrounds should design agents for various tasks such as automated negotiation (e.g. how should a person design a representative agent to negotiate on her behalf?) and social choice (e.g. how should a person design a voting bot to represent her in online voting systems?).

People are increasingly interacting with conversational agents in various settings and for a variety of reasons, as the market size of those agents keeps on growing every year. Through a first-of-its-kind human study (N = 41), consisting of both expert designers, computationally-oriented designers, and otherwise, the authors demonstrate a few key advantages and limitations of BP in the realm of conversational agents and propose its consideration as an alternative to the classic dialog graph technique.

This paper aims to propose a new framework on prioritizing and deployment of design for additive manufacturing (DfAM) strategies to an industrial component using Fuzzy TOPSIS multiple criteria decision-making (MCDM) techniques. The proposed framework is then applied to an automotive component, and the results are discussed and compared with existing design.

Eight DfAM design alternatives associated with eight design criteria have been identified for framing new DfAM strategies. The prioritization order of the design alternatives is identified by Fuzzy TOPSIS MCDM technique through its closeness coefficient. Based on Fuzzy TOPSIS MCDM output, each of the design alternatives is applied sequentially to an automobile component as a case study. Redesign is carried out at each stage of DfAM implementation without affecting the functionality.

On successful implementation of proposed framework to an automotive component, the mass is reduced by 43.84%, from 0.429 kg to 0.241 kg. The redesign is validated by finite element analysis, where von Mises stress is less than the yield stress of the material.

The proposed DfAM framework and strategies will be useful to designers, R&D engineers, industrial practitioners, experts and consultants for implementing DfAM strategies on any industrial component without impacting its functionality.

To the best of the authors’ knowledge, the idea of prioritization and implementation of DfAM strategies to an automotive component is the original contribution.

This paper aims to propose a generative design method combined with meta-heuristic algorithm for automating and optimizing the floor layout of modular buildings using typical standardized module units, which are the room module, the corridor module and the stair module.

The integrated framework involves the generative design method and optimization for modular construction. The generative rules are provided by geometric relationships and functionalities of the module units. An evaluation function of the generated floor plans is also presented by the combination of project cost and cost penalties for the geometric features. The multi-population genetic algorithm (MPGA) method is provided for the optimization of the combination of costs.

The proposed MPGA method is demonstrated fast and efficient at discovering the globally optimal solution. The results indicate that when the unit price of modules is high, the transportation distance is long, or the land cost is high, the layout cost, which related to the symmetry, the compactness and the energy is tend to be lower, making the optimal layout economical.

This paper presented an integrated framework of generative floor layout and optimization for modular construction by using typical module units. It fulfills the need for automated layout generation with repetitive units and corresponding assessment during the early design stage.

This study provides a configurational examination of how policy designs influence the innovation performance of the emergency industry in China.

This study employs the Data Envelopment Analysis Malmquist index (DEA-Malmquist) to quantify the innovation performance of the emergency industry and then codes the innovation policies to calculate the syntactic components based on institutional grammar tools (IGTs). The configurations of syntactic components were determined by applying the fuzzy-set qualitative comparative analysis (fsQCA).

The results indicate that rules- and norms-oriented policy designs would improve the innovation performance of China's emergency industry. In the developed provinces, the “Deontic” and “aIm” combinations in the policy are useful for improving performance. In the developing provinces, the ambiguity of the “aIm” and “Context” conditions in the policy is leading to low performance. Additionally, a lack of strategy-oriented policy design would also result in poor performance.

Most previous studies used substitute variables to understand policy impacts. This study contributes to identifying the impacts of the syntactic components of policy designs on the innovation performance of the emergency industry. The findings can assist policymakers in developing more effective policies to stimulate innovation development in the emergency industry.

To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.

First, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.

This method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.

The TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.

This paper aims to systematically understand the development of rapid setup, quantitatively analyze the landscape and reveal new trends and challenges.

Based on 192 literature studies (1987–2021) collected from Scopus and Google Scholar, the papers are classified by: publication time and source; research type and data analysis of papers; pattern of authorship and country; sector-wise focus of the paper; improvement method used in the setup. And CiteSpace is used to analyze the cooccurrence and timeline of keywords.

There has been substantial progress in the past 35 years, including the rapid growth in the number of papers, the expansion in different disciplines, the participation of developing countries, the application in the service industry and the significant impact of setup on cost. And there are still some deficiencies.

There is concern that Google Scholar lacks the quality control needed for its use as a bibliometric tool. Future work is encouraged to conduct an in-depth discussion on high-quality papers.

In small batch production, rapid setup is increasingly essential. Clarifying the research focus and main improvement methods is of great significance for enterprises to meet the changing market needs.

To the best of the authors’ knowledge, this study is the first literature review on rapid setup. It is decided to consider a detailed set of data for better introspection and trace the history reflections and the research future in setup time.

A combustor design is a particularly important and difficult task in the development of gas turbine engines. During studies for accurate and easy combustor design, reasonable design methodologies have been established and used in engine development. The purpose of this paper is to review the design methodology for combustor in development of advanced gas turbine engines. The advanced combustor development task can be successfully achieved in less time and at lower cost by adopting new and superior design methodologies.

The review considers the main technical problems (combustion, cooling, fuel injection and ignition technology) in the development of modern combustor design and deals with combustor design methods by dividing it into preliminary design, performance evaluation, optimization and experiment. The advanced combustion and cooling technologies mainly used in combustor design are mentioned in detail. In accordance with the modern combustor design method, the design mechanisms are considered and the methods used in every stage of the design are reviewed technically.

The improved performances and strict emission limits of gas turbine engines require the application of advanced technologies when designing combustors. The optimized design mechanism and reasonable performance evaluation methods are very important in reducing experiments and increasing the effectiveness of the design.

This paper provides a comprehensive review of the design methodology for the advanced gas turbine engine combustor.

Access to services for consumers with disabilities (CwD) has gained increased attention from researchers and service providers in recent years. Consequently, ensuring that services are designed and maintained in a manner that is more inclusive and accessible to CwD has become imperative. However, academic literature is fragmented and thus, this study aims to provide a state-of-the-art synthesis for further theoretical development.

This study reviews 77 relevant articles in the domain using a multidisciplinary review following the PRISMA protocol, and a thematic analysis was conducted.

The study thoroughly synthesizes the theories, contexts and methods used in the extant literature. Next, the study presents a new theoretical framework with four broader dimensions: beyond regulations, towards accessibility, value co-creation, inclusion of CwD and role of stakeholders. Furthermore, it highlights the related sub-dimensions attributed to the service design stages (planning, usage and post-usage). Based on this, the study offers critical avenues for future research using the Double Diamond framework.

The study contributes significantly to service design literature for CwD and transformative service research by developing a new consolidated theoretical framework. The findings should direct service providers towards better service designs in related fields. Socially, the study has implications for promoting accessibility and inclusion for CwD, while providing them the freedom of choice.

The main purpose of this study was to propose theoretical calculation models to evaluate the theoretical bending strengths of welded wide-flange section steel beams with local buckling at elevated temperatures.

Steady-state tests using various test parameters, including width-thickness ratios (Class 2–4) and specimen temperatures (ambient temperature, 400, 500, 600, 700, and 800°C), were performed on 18 steel beam specimens using roller supports to examine the maximum bending moment and bending strength after local buckling. A detailed calculation model (DCM) based on the equilibrium of the axial force in the cross-section and a simple calculation model (SCM) for a practical fire-resistant design were proposed. The validity of the calculation models was verified using the bending test results.

The strain concentration at the local buckling cross-section was mitigated in the elevated-temperature region, resulting in a small bending moment degradation after local buckling. The theoretical bending strengths after local buckling, evaluated from the calculation models, were in good agreement with the test results at elevated temperatures.

The effect of local buckling on the bending behaviour after the maximum bending strength in high-temperature regions was quantified. Two types of calculation models were proposed to evaluate the theoretical bending strength after local buckling.

Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.